|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||On the Fractal Nature of Local Optima Networks|
|Citation:||Thomson S, Verel S, Ochoa G, Veerapen N & McMenemy P (2018) On the Fractal Nature of Local Optima Networks In: , Springer. EvoCOP 2018 - The 18th European Conference on Evolutionary Computation in Combinatorial Optimisation, 4.4.2018 - 6.4.2018, Parma, Italy.|
|Series/Report no.:||Lecture Notes in Computer Science|
|Conference Name:||EvoCOP 2018 - The 18th European Conference on Evolutionary Computation in Combinatorial Optimisation|
|Conference Location:||Parma, Italy|
|Abstract:||A Local Optima Network represents fitness landscape connectivity within the space of local optima as a mathematical graph. In certain other complex networks or graphs there have been recent observations made about inherent self-similarity. An object is said to be self-similar if it shows the same patterns when measured at different scales; another word used to convey self-similarity is fractal. The fractal dimension of an object captures how the detail observed changes with the scale at which it is measured, with a high fractal dimension being associated with complexity. We conduct a detailed study on the fractal nature of the local optima networks of a benchmark combinatorial optimisation problem (NK Landscapes). The results draw connections between fractal characteristics and performance by three prominent metaheuristics: Iterated Local Search, Simulated Annealing, and Tabu Search.|
|Status:||Book Chapter: author post-print (pre-copy editing)|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.|
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